Forward projection cylinder volume method

ABSTRACT

A method of generating a template image includes: receiving an input from a user representing identifications of an object in different respective slices of a volumetric image; using the input to determine a volume-of-interest (VOI) that includes voxels in a subset of the volumetric image; and determining the template image using at least some of the voxels in the VOI, wherein the act of determining the template image comprises performing a forward projection of the at least some of the voxels in the VOI using a processor. An image processing method includes: obtaining a volumetric image; performing forward projection of voxels in the volumetric image from different positions onto a first plane using a processor; and summing projections on the first plane resulted from the forward projection from the different positions to create a first image slice in the first plane.

FIELD

This application relates generally to imaging, and more particularly, tosystems and methods for segmentation of radiopaque structures in images.

BACKGROUND

Radiotherapy has been used in the treatment of tumors, such as tumors inlung and abdomen. Implanted markers, such as radio opaque fiducials,have been used in radiotherapy for target localization. In particular,in radiotherapy, precise delivery of the treatment dose is crucial inorder to maximize the ratio between tumor dose and normal tissue dose.To achieve this goal x-ray visible markers may be implanted in or near atumor. It allows use of the projected marker trajectory in x-ray imagesfor image-guided radiotherapy (IGRT).

Sometimes, a marker may not have the simple shape such as the goldcylinder or BB. One example of such marker is the thin flexibleVisicoil™ markers that are implanted in or around a tumor in anatomicalsites such as lung, liver, and pancreas for the purpose of IGRT. Themain advantage of Visicoil™ is reduced invasiveness due to its smalldiameter and less chance of migration in soft tissue because they aredesigned to coil up and engage the surrounding tissue after beingimplanted in the form of a straight wire. However because of thevariability of the surrounding tissue, instead of completely coiling up,the marker may assume an irregular and unpredictable shape after beingimplanted in the anatomical three-dimensional space. In some cases,robust tracking of the fiducial can be a challenge because it shows upin varying extended shapes in the X-ray projections acquired fromdifferent orientations.

SUMMARY

In accordance with some embodiments, an image processing methodincludes: obtaining an input image; enhancing an object in the inputimage; and after the input image is enhanced, applying a low-pass filterusing a processor to obtain a processed image.

In accordance with other embodiments, a computer product includes anon-transitory medium storing a set of instructions, an execution ofwhich causes a method to be performed, the method comprising: obtainingan input image; enhancing an object in the input image; and after theinput image is enhanced, applying a low-pass filter to obtain aprocessed image.

In accordance with other embodiments, a method of generating a templateimage includes: receiving an input from a user representingidentifications of an object in different respective slices of avolumetric image; using the input to determine a volume-of-interest(VOI) that includes voxels in a subset of the volumetric image; anddetermining the template image using at least some of the voxels in theVOI, wherein the act of determining the template image comprisesperforming a forward projection of the at least some of the voxels inthe VOI using a processor.

In accordance with other embodiments, a computer product includes anon-transitory medium storing a set of instructions, an execution ofwhich causes a method to be performed, the method comprising: receivingan input from a user representing identifications of an object indifferent respective slices of a volumetric image; using the input todetermine a volume-of-interest (VOI) that includes voxels in a subset ofthe volumetric image; and determining a template image using at leastsome of the voxels in the VOI, wherein the act of determining thetemplate image comprises performing a forward projection of the at leastsome of the voxels in the VOI.

In accordance with other embodiments, an image processing methodincludes: obtaining a volumetric image; performing forward projection ofvoxels in the volumetric image from different positions onto a firstplane using a processor; and summing projections on the first planeresulted from the forward projection from the different positions tocreate a first image slice in the first plane.

In accordance with other embodiments, a computer product includes anon-transitory medium storing a set of instructions, an execution ofwhich causes a method to be performed, the method comprising: obtaininga volumetric image; performing forward projection of voxels in thevolumetric image from different positions onto a first plane using aprocessor; and summing projections on the first plane resulted from theforward projection from the different positions to create a first imageslice in the first plane.

Other and further aspects and features will be evident from reading thefollowing detailed description of the embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings illustrate the design and utility of embodiments, in whichsimilar elements are referred to by common reference numerals. Thesedrawings are not necessarily drawn to scale. In order to betterappreciate how the above-recited and other advantages and objects areobtained, a more particular description of the embodiments will berendered, which are illustrated in the accompanying drawings. Thesedrawings depict only typical embodiments and are not therefore to beconsidered limiting of its scope.

FIG. 1 illustrates a radiation system that may be used to implement oneor more embodiments described herein;

FIG. 2 is a flow diagram illustrating a method for template matching inaccordance with some embodiments;

FIGS. 3-4 illustrate a method of generating a template in accordancewith some embodiments;

FIG. 5 illustrates a method of processing an input image in accordancewith some embodiments;

FIG. 6 illustrates an example of a match score surface in accordancewith some embodiments;

FIG. 7 illustrates a threshold parameter that affects false detectionprobability and probability of missing a target;

FIG. 8 illustrates a technique for performing tracking without usingimplanted markers;

FIGS. 9A-9C illustrate a technique for generating a digitaltomosynthesis image using a volumetric image in accordance with someembodiments; and

FIG. 10 illustrates a computer system with which embodiments describedherein may be implemented in accordance with some embodiments.

DESCRIPTION OF THE EMBODIMENTS

Various embodiments are described hereinafter with reference to thefigures. It should be noted that the figures are not drawn to scale andthat elements of similar structures or functions are represented by likereference numerals throughout the figures. It should also be noted thatthe figures are only intended to facilitate the description of theembodiments. They are not intended as an exhaustive description of theinvention or as a limitation on the scope of the invention. In addition,an illustrated embodiment needs not have all the aspects or advantagesshown. An aspect or an advantage described in conjunction with aparticular embodiment is not necessarily limited to that embodiment andcan be practiced in any other embodiments even if not so illustrated.

FIG. 1 illustrates a radiation system 10 that may be used to implementone or more embodiments described herein. The system 10 includes agantry 12, a patient support 14 for supporting a patient 28, and acontrol system 18 for controlling an operation of the gantry 12. Thesystem 10 also includes a radiation source 20 that projects a beam 26 ofradiation towards the patient 28 while the patient 28 is supported onsupport 14, and an imager 100 located at an operative position relativeto the source 20 (e.g., under the support 14). The radiation source 20can be configured to generate a cone beam, a fan beam, or other types ofradiation beams in different embodiments.

In the illustrated embodiments, the radiation source 20 is a diagnosticradiation source for providing diagnostic energy. In such cases, theimager 100 is configured to receive diagnostic radiation and generateimage signals in response thereto. In other embodiments, in addition tobeing a diagnostic radiation source, the radiation source 20 is also atreatment radiation source for providing treatment energy. In suchcases, the imager 100 is configured to selectively receive diagnosticradiation or treatment radiation and generate image signals in responsethereto. In further embodiments, instead of being a diagnostic radiationsource, the radiation source 20 is a treatment radiation source. In suchcases, the imager 100 is configured to receive treatment radiation andgenerate image signals in response thereto. In the embodiments in whichthe radiation source 20 is configured to deliver treatment radiation,the system 10 may optionally further include a collimator for changing acharacteristic (e.g., shape) of the radiation beam.

In some embodiments, the treatment energy is generally those energies of160 kilo-electron-volts (keV) or greater, and more typically 1mega-electron-volts (MeV) or greater, and diagnostic energy is generallythose energies below the high energy range, and more typically below 160keV. In other embodiments, the treatment energy and the diagnosticenergy can have other energy levels, and refer to energies that are usedfor treatment and diagnostic purposes, respectively. In someembodiments, the radiation source 20 is able to generate X-ray radiationat a plurality of photon energy levels within a range anywhere betweenapproximately 10 keV and approximately 20 MeV. Radiation sources capableof generating X-ray radiation at different energy levels are describedin U.S. patent application Ser. No. 10/033,327, entitled “RADIOTHERAPYAPPARATUS EQUIPPED WITH AN ARTICULABLE GANTRY FOR POSITIONING AN IMAGINGUNIT,” filed on Nov. 2, 2001, and U.S. patent application Ser. No.10/687,573, entitled “MULTI-ENERGY X-RAY SOURCE,” filed on Oct. 15,2003. In the illustrated embodiments, the radiation source 20 is coupledto a ring gantry and is located within a bore. In other embodiments, theradiation source 20 may be coupled to an arm gantry.

In the illustrated embodiments, the control system 18 includes aprocessor 54, such as a computer processor, coupled to a control 40. Thecontrol system 18 may also include a monitor 56 for displaying data andan input device 58, such as a keyboard or a mouse, for inputting data.In the illustrated embodiments, the gantry 12 is rotatable about thepatient 16, and during an imaging and/or a treatment procedure, thegantry 12 rotates about the patient 28 (as in a CT procedure and/or anarch-therapy). In other embodiments, the gantry 12 does not rotate aboutthe patient 28 during a procedure. In such case, the gantry 12 may befixed, and the patient support 14 is rotatable. The operation of theradiation source 20 and the gantry 12 (if the gantry 12 is rotatable)are controlled by the control 40, which provides power and timingsignals to the radiation source 20, and controls a rotational speed andposition of the gantry 12, based on signals received from the processor54. Although the control 40 is shown as a separate component from thegantry 12 and the processor 54, in alternative embodiments, the control40 can be a part of the gantry 12 or the processor 54.

It should be noted that the system 10 is not limited to the exampledescribed above, and that the system 10 may have other configurations inother embodiments. For example, in other embodiments, the system 10 mayhave different shapes. In other embodiments, the system 10 may havedifferent ranges of motions and/or degrees of freedom. For example, inother embodiments, the radiation source 20 may be rotatable about thepatient 28 completely through a 360° range, or partially through a rangethat is less than 360°. Also, in other embodiments, the radiation source20 is translatable relative to the patient 28. In still furtherembodiments, the system 10 may be any imaging system that has imagingcapability.

FIG. 2 is a flow diagram illustrating a method 200 for template matchingin accordance with some embodiments. The method 200 includes a templategeneration process 202, an imaging process 204, and a template matchingprocess 206.

As shown in the figure, in the template generation process 202, avolumetric image 210 (such as, a CT image) and information 212 regardingcontoured structure(s) are used to provide one or more template images214. In the illustrated embodiments, the volumetric image 210 may beobtained from a planning session. In other embodiments, the volumetricimage 210 may be obtained during a diagnostic session, or a treatmentsession. In some embodiments, the volumetric image 210 may have a pixelresolution of 1 mm or less than 1 mm. In other embodiments, thevolumetric image 210 may have a pixel resolution greater than 1 mm.Also, in some embodiments, the slices of the volumetric image 210 mayhave a spacing that is 2.5 mm or less, and more preferably 1.25 mm orless.

The information 212 regarding contoured structure(s) may be obtainedfrom a physician or a technician, who provides contour(s) aroundobject(s) of interest in the image 210. In some embodiments, theinformation 212 regarding the contoured structure(s) may be thecontour(s) drawn by a person who reviewed the image 210, and/or dataregarding the contour(s). In other embodiments, instead of obtaining theinformation 212 from a person (user) who inputs the information 212, theinformation 212 may be obtained from a device. For example, the personreviewing the image 210 may input the information regarding thecontoured structure(s) into a device through a user interface, whereinthe device may be a computer, a handheld device, a storage device, orany of other types of device that is capable of receiving data. In suchcases, the information 212 may be obtained by retrieving the storedinformation 212 from the device.

In the imaging process 204, an input image 220 is used to generate aprocessed image 222. In some embodiments, the input image 220 may be animage obtained before a treatment session, such as during a patientsetup. In other embodiments, the input image 220 may be obtained duringa treatment session, such as during an activation of a radiation beam,or between delivery of radiation beams. In some cases, the input image220 may be an online image, such as an online projection image. In theillustrated embodiments, the imaging process 204 may involve one or morespatial filters that are applied to the input image 220 to generate theprocessed image 222. In some embodiments, one of the spatial filters maybe configured (e.g., at least partially defined) by a user input 240,such as a fiducial width. Also, in some embodiments, the input image 220may be a subset of the original image. For example, the input image 220may be a region of interest (ROI) that is within the original inputimage. The ROI may be selected manually by a user who reviews the inputimage. In some embodiments, the ROI may be determined automatically as asearch area expanded by dimensions (e.g., x-dimension and y-dimension)of the template image 214. The search area in the input image 220 may becentered at an expected target position, and may have dimensions thatcorrespond with motion margins. In some cases, the expected targetposition may be determined from planning data. For example, the planningdata may include information regarding a treatment isocenter position,and contoured structures representing a treatment volume. Also, in somecases, the motion margins may be obtained from planning data. Forexample, there may be a 4D CT of the tumor, which shows the extent ofits motion. In other embodiments, the input image 220 may be the entireoriginal image.

In the template matching process 206, the processed input image 222 andthe template image(s) 214 are processed to determine whether there is amatch, and if so, determine a position of an object based on the match.

FIGS. 3-4 illustrate a method 300 of generating a template (such as thetemplate image 214 of FIG. 2) in accordance with some embodiments. Themethod 300 may be used to implement the template generation process 202of FIG. 2 in some embodiments. As shown in FIG. 3, the method 300includes receiving an input from a user representing an identificationof the object by the user (Item 302). In some embodiments, the user mayexamine a volumetric image (such as one or more slices of the volumetricimage 210 in FIG. 2) to identify object(s) of interest. The user maythen create a contour around an object of interest by some means, suchas by using a graphical user interface. In some embodiments, the createdcontour and/or data associated therewith may be an example of the input212 shown in FIG. 2. In some cases, the volumetric image 210 may includean image of an irregularly-shaped marker 400 (FIG. 4). In such cases,the user may examine different slices of the volumetric image 210 toidentify the marker 400 as it appears in the different slices, and thendraw a contour 402 around the marker 400 in each of the different slicesof the volumetric image 210. In some embodiments, item 302 in the method300 of FIG. 3 may be accomplished by a device (e.g., a processor, suchas the processor 54, or another processor) receiving the input from theuser that represents the identification of the object (e.g., marker400). In other embodiments, the user input 212 representing theidentification of the object may be stored in a device, and item 302 maybe accomplished by the same device that stores the input 212 (e.g., thedevice itself may retrieve the stored input 212). In furtherembodiments, the user input 212 representing the identification of theobject mat be stored in a first device, and item 302 may be accomplishedby a second device that retrieves the stored input 212 from the firstdevice.

Returning to FIG. 3, next, in the method 300, the input (e.g., the input212) obtained from item 302 is used by a processor (e.g., the processor54, or another processor) to determine a volume-of-interest (VOI) thatincludes voxels of the volumetric image (Item 304). In some embodiments,the VOI includes the voxels that are within the contour(s) 402 drawn bythe user in each of the slices of the volumetric image 210. Also, insome embodiments, the VOI may include additional voxels that are outsidethe contour(s) 402. For example, in some embodiments, the VOI mayinclude voxels from the volumetric image 210 that are a certainprescribed distance from the drawn contour(s) 402. In other embodiments,the VOI may include voxels from the volumetric image 210 that are withina defined three-dimensional spatial geometry. For example, as shown inFIG. 4, a cylindrical geometry 420 (an example of the VOI) may bedefined based on the contour(s) 402, such that all of the voxels withinthe contour(s) 402 are within the cylindrical geometry 420. In somecases, the cylindrical geometry 420 may further be defined as having acircular cross section, and a longitudinal axis 422 that isperpendicular to the circular cross section and that is parallel to (oraligned with) a rotational axis of a gantry of an imaging device (e.g.,the rotational axis 110 in the system 100 of FIG. 1). In otherembodiments, the three-dimensional spatial geometry may have differentshapes from the cylindrical geometry. Also, in other embodiments, thethree-dimensional spatial geometry may be defined using other criteria.

Returning to the method 300 of FIG. 3, next, the processor determines(e.g., calculates, generates, derives, etc.) a template (such as thetemplate image 214 in FIG. 2) using at least some of the voxels in theVOI 420 (Item 306). In some embodiments, the determination of thetemplate may be accomplished by a processor (e.g., processor 54, oranother processor) performing a forward projection of the at least someof the voxels in the VOI 420. By means of non-limiting examples, theforward projection may be a forward maximum intensity projection, aforward average projection, or a forward median projection, of the atleast some of the voxels in the VOI 420. In some embodiments, before theforward projection is performed, the processor may also resample voxelsin the VOI 420 into image planes 430 that are parallel to a plane of theinput image (e.g., input image 220). Thus, the resampling of the voxelsin the VOI 420 may be based on the orientation of the input image 220.In such cases, depending the gantry angle at which the input image 220is generated, the orientation of the image planes 430 for the resamplingof the voxels may be adjusted to correspond with the orientation of theinput image 220.

As shown in the above embodiments, defining the VOI 420 is advantageousbecause it limits the number of voxels for processing (e.g., forwardprojection) to be a certain subset of the original volumetric image.This, in turn, results in the template image 214 having a dimension thatcorresponds to the defined VOI 420. Accordingly, the resulting templateimage 214 will have a dimension that covers the object(s) of interest,while other objects outside the VOI 420 will be excluded from beingincluded in the template image 214. This is also advantageous in that itlimits the template image 214 to have a size that is large enough forcovering the object(s) of interest for tracking purpose. In someembodiments, the sizing of the template image 214 is determined andaccomplished automatically by the processor (e.g., the processor 54, oranother processor) based on the input 212 from the user.

In some embodiments, the template image 214 determined from item 306 maybe stored in a non-transitory medium for later processing. Alternativelyor additionally, the template image 214 may be displayed in a screen forallowing a user to see. Also, in some embodiments, the processor (e.g.,the processor 54, or another processor) may determine a plurality oftemplate images 214 using the above technique for different gantryangles. For example, the processor may determine a set of templateimages 214 that correspond to 120 gantry angles with 3° spacing. In oneimplementation, the processor may generate only half the number oftemplate images 214 (e.g., covering 180° range), and then generates therest by flipping the template images 214 horizontally. The templateimages 214 may be stored in a non-transitory medium for laterprocessing, and/or displayed in a screen for allowing a user to see.Furthermore, in some embodiments, any parameters and/or input that areinvolved in the method 300 may be stored in a non-transitory medium forlater retrieval and/or processing. For examples, parameters and/or inputthat are used to define the VOI 420 may be stored in a non-transitorymedium in some embodiments.

Returning to FIG. 2, as discussed, the method 200 for template matchingalso includes the imaging process 204, which involves obtaining theinput image 220, and processing the input image 220 to obtain theprocessed image 222. In some embodiments, the input image 220 isprocessed into the processed image 222 so that the processed image 222has a desirable feature for comparison with the template image 214.Various techniques may be employed to process the input image 220 sothat it has a desirable feature for comparison with the template image214. In some embodiments, the processing of the input image 220 mayinvolve applying a first spatial filter and a second spatial filter tothe input image 220 to obtain the processed image 222. FIG. 5illustrates a method 500 for processing the input image 220 inaccordance with some embodiments. As shown in the figure, a first filter510 may be applied to the input image 220 to enhance an object in theinput image 220. After the first filter 510 has been applied, a secondfilter 520 may be applied so that the processed image 222 has a degreeof resolution that corresponds (e.g., matches or closely resembles) withthat of the template image 214.

In the illustrated embodiments, the first filter 510 is a rolling ballfilter. In one implementation, a rolling ball filter may be defined atleast partially by a ball diameter w_(b)=(c²+w_(p) ²)^(1/2), whereinw_(p) is a fiducial width (e.g., a width, such as a cross sectionaldimension, of the marker 400), and c may be any constant. In someembodiments, w_(p) may be 0.35 mm for a Visicoil wire that is not coiledup, or may be 2.0 mm for a Visicoil wire that is coiled up. In otherembodiments, w_(p) may be 3.0 mm for a coiled up embolization coil. Infurther embodiments, w_(p) may be a diameter of a cylindrical gold seed,such as 0.8 mm. It should be noted that w_(p) should not be limited tothe above examples, and that w_(p) may have other values that aredifferent from the above examples. Also, in some embodiments, c may be avalue that is anywhere between 0.1 mm and 1 mm, and more preferably,between 0.2 mm and 0.5 mm, and more preferably, between 0.3 mm and 0.4mm (e.g., 0.35 mm). In other embodiments, c may be other valuesdifferent from those described. In some embodiments, the rolling ballfilter may be applied to the input image 220 to enhance an object (e.g.,the marker 400, or a tissue structure) relative to its surroundingobjects. In other embodiments, the rolling ball filter may be applied tothe input image 220 to enhance a boundary of the object (e.g., aboundary of tissue structure).

Also, in the illustrated embodiments, the second filter 520 is alow-pass filter. In one implementation, the low-pass filter may bedefined at least partially by two parameters w_(x), w_(y). The parameterw_(x) is used to configure the input mage 220 so that the processedimage 222 has a resolution in the x-direction that corresponds with apixel size of the volumetric image 210 (that was used to generate thetemplate image 214). The parameter w_(y) is used to configure the inputimage 220 so that the processed image 222 has a resolution in they-direction that corresponds with a slice spacing of the volumetricimage 210 (that was used to generate the template image 214). In someembodiments, w_(x) may be determined as a constant (e.g., 0.3, or any ofother values) times a pixel size in the volumetric image 210. Also, insome embodiments, w_(y) may be determined as a constant (e.g., 0.3, orany of other values) times a slice spacing of the volumetric image 210.Furthermore, in some embodiments, the low-pass filter may be a Gaussianshaped low-pass filter. In one implementation, the Gaussian shapedlow-pass filter may be specified by 1 standard deviation widths in thex-direction and the y-direction with respect to the input image 220.

It should be noted that there may be other parameter(s) for defining thelow-pass filter in other embodiments. For examples, inaddition/alternative to the parameters described above, other filterparameter(s) may include SAD, SDD, detector pixel size, or combinationthereof.

In other embodiments, each of the first filter 510 and the second filter520 may be any of other types of filters that are different from theexamples described.

Returning to FIG. 2, after the input image 220 has been processed toprovide the processed image 222, and after the template image(s) 214 hasbeen obtained, the processed image 222 may then be compared with thetemplate image(s) 214 in the template matching process 206. In someembodiments, the input image 220 may be obtained by a processor (e.g.,the processor 54, or another processor) receiving the input image 220from an imager or a storage device. Such may be accomplished before atreatment session, as in a patient setup, in which cases, the processedimage 222 may be compared with the template image 214 to identifyobject(s) of interest for positioning the patient. In other embodiments,the processed image 222 may be obtained, and the comparison between theprocessed image 222 and the template image 214 may be performed, duringa treatment session between deliveries of radiation beams. In suchcases, the processed image 222 may be used to reposition the patientbetween deliveries of radiation beams. In further embodiments, theprocessed image 222 may be obtained, and the comparison between theprocessed image 222 and the template image 214 may be performed, duringa delivery of a radiation beam. In such cases, the result of thecomparison between the processed image 222 and the template image 214may be used for substantially real-time tracking of the object(s) ofinterest.

In some embodiments, when comparing the processed image 222 and thetemplate image 214, the processor determines the template image 214having a plane that is parallel to the plane of the processed image 222.Thus, in some embodiments, the template image 214 (that is used forcomparison with the processed image 222) is the one derived fromresampled voxels that lie in the image planes 430 having an orientationthat is parallel to the plane of the processed image 222 or the inputimage 220 (see FIG. 4). As discussed, in some embodiments, the processormay generate a set of template images 214 that correspond with differentgantry angles ahead of time, and stores the template images 214 in anon-transitory medium. In such cases, during the template matchingprocess 206, the processor selects the template image 214 from the sethaving a gantry orientation that corresponds (e.g, that is the same, orthe closest) with the gantry orientation at which the input image 220 isobtained.

In other embodiments, for each input image 220, the processor may selectseveral template images 214 covering gantry angles that are adjacent tothe gantry angle at which the input image 220 is generated. For example,if the input image 220 is generated at a gantry angle of 30°, inaddition to selecting the template image 214 having a correspondinggantry angle of 30°, the processor may also select the template images214 having corresponding gantry angles that are within a prescribedrange from 30° (e.g., template images 214 that are within gantry angles30°±10°). Such technique is advantageous because the object of interestmay have rotated slightly since the time the template images 214 weregenerated. Checking other gantry angles allows such rotation to beaccounted for when trying to find a template image 214 that best matchthe input image 220/processed image 222. Also, in some embodiments, theabove technique may provide a way to estimate an amount of rotation.

Various techniques may be employed to compare the processed image 222with the template image 214. For example, a processor (e.g., theprocessor 54, or another processor) may be configured to perform crosscorrelation, normalized cross correlation, or mutual information,between the processed image 222 and the template image 214 in differentembodiments. Also, in some embodiments, the processor may be configuredto determine a degree of similarity between the processed image 222 andthe template image 214.

In one implementation, the processor may determine match scores betweenthe template image 214 and the processed image 222 at different offsetsrelative to each other. For example, the template image 214 may bepositioned (mathematically) at different offsets relative to theprocessed image 222, covering a search ROI. As shown in FIG. 6, thematch scores may define a match score surface 600 over a search region.As shown in the figure, the match score surface 600 may have a peak 602and at least one sidelobe 604. In some embodiments, the values in thematch score surface 600 may optionally be normalized, with the highestpeak 602 having a value of 1.0.

In some cases, the fact that there is a peak in the match score surface600 may not represent that the object(s) of interest is in the processedimage 222. In other words, the peak 502 in the match score surface 600may not represent a “true” match between the processed image 222 and thetemplate image 214. This is because the above technique of determiningthe match score surface 600 will always result in a peak 602 in thematch score surface 600, regardless of whether there is a “true match”.Thus, in some embodiments, it may be desirable to determine whether thepeak 602 represents a match between the processed image 222 and thetemplate image 214.

To accomplish this, in some embodiments, the processor may determine howmuch the peak 602 stands out relative to the sidelobe(s) 604. Forexample, in one implementation, the processor may be configured todetermine a peak-to-sidelobe ratio by dividing the value of the peak 602by the value of the sidelobe 604. In another embodiment, the processormay determine a standard deviation of the sidelobe(s) 604, anddetermining a peak-to-sidelobe ratio by dividing the value of the peak602 by the standard deviation of the sidelobe(s) 604. After thepeak-to-sidelobe ratio is determined, the processor may then compare thepeak-to-sidelobe ratio with a threshold to determine whether there is amatch between the processed image 222 and the template image 214. If thepeak-to-sidelobe ratio exceeds the threshold, then the processor maydetermine that the target (object of interest) is present. Otherwise,the processor may determine that the target is absent. If the target ispresent, the position of the peak 602 may be used as the position of thetarget. In some embodiments, the threshold may be determined based onsidelobe statistics for a given image, such as that shown in FIG. 7 anddiscussed herein. Alternatively, the threshold may be determined basedon sidelobe statistics for multiple images.

Also, as discussed, in some embodiments, the processor may compare theprocessed image 222 with several template images 214 that are adjacent(in terms of orientation/gantry angles) next to the processed image 222to account for slight rotation of the object of interest. In such cases,for each of the template images 214, the processor may determine acorresponding peak-to-sidelobe ratio. The processor may also select thetemplate image having the highest peak-to-sidelobe ratio as the matchedtemplate image, and use the position of the peak 602 in such templateimage as the position of the target.

In one or more embodiments, the processor (e.g., the processor 54, oranother processor) may be configured to automatically identify thesidelobe(s) 604. For example, in some embodiments, the processor may beconfigured to exclude the peak 602 and its vicinity from the match scoresurface 600, and the remaining surface will have the sidelobe(s) 604,and not the peak 602. In some embodiments, the processor may determine amask to exclude the peak 602. For example, the processor may determinethe mask by cross correlating the template image 214 with itself atdifferent offsets to obtain an autocorrelation surface. Then theprocessor identifies locations where the autocorrelation surface exceedsa threshold value. For example, the threshold value may be anywherebetween 0.1 and 0.3, or more preferably anywhere between 0.15 and 0.25(e.g., 0.2). All values in the match score surface 600 exceeding thethreshold value will be parts of an exclusion zone. When the exclusionzone is applied to the match score surface 600, the peak 602 and itsvicinity will be removed.

Alternatively, the processor may identify locations where theautocorrelation surface is below a threshold value. For example, thethreshold value may be anywhere between 0.1 and 0.3, or more preferablyanywhere between 0.15 and 0.25 (e.g., 0.2). All values in the matchscore surface 600 that are below the threshold value will be parts of anacceptance zone. When the acceptance zone is applied to the match scoresurface 600, the sidelobe(s) 604 will remain as parts of the remainingsurface, while the peak 602 and its vicinity will be removed. In suchcases, the mask represents the acceptance zone, not the exclusion zone.

In one or more embodiments, the mask (which may represent an exclusionzone or an acceptance zone) may be stored in a non-transitory medium.For example, the mask may be saved as a list of (X, Y) coordinates, with(0, 0) referenced to the peak position.

As shown in FIG. 7, the threshold determines the probability P_(FD) offalsely detecting a target at a non-target point in the search region.The threshold also determines the probability P_(A) of missing a targetthat is in fact present.

In the above embodiments, the object(s) of interest has been describedwith reference to the marker 400. The marker 400 may have an elongateconfiguration, a spherical configuration, an elliptical configuration, arandom three-dimensional configuration, or any of other configurations.In other embodiments, the object(s) of interest may be a plurality ofmarkers. In such cases, the VOI (e.g., the cylindrical geometry 420) mayinclude voxels that are within contours 402 of the markers drawn by theuser in each of the slices of the volumetric image 210. Accordingly, theresulting template image(s) 214 obtained from the method 300 of FIG. 3will include images of the markers 400. When such template image(s) 214is used in the template matching process 206 of FIG. 2, the processedimage 222 will be compared with the template image(s) based on the groupof markers 400 as if they are a single object.

Also, in other embodiments, the object(s) of interest may be a tissuestructure (markerless fiducial). In such cases, the template image(s)214 may be generated so that it has features that correspond with thetissue structure. For example, as shown in FIG. 8, in some embodiments,the template image 214 may include a region 802 having a shape thatresembles the tissue structure. The template image 214 may also includea first layer/region 804 surrounding the region 802, and a secondlayer/region n806 surrounding the first layer/region 804. As shown inthe figure, the regions 802, 804, 806 in the template image 214 havedifferent respective colors/gray-scales.

Various techniques may be employed to generate the template image 214.In some embodiments, a person may review slices of a volumetric image(e.g., the volumetric image 210 of FIG. 2), and identify object ofinterest. The person may then create contours around the object ofinterest in the respective slices of the volumetric image. In someembodiments, the processor (e.g., the processor 54, or anotherprocessor) may be configured to receive the created contours as input212 from the user, and automatically create a three-dimensional modelbased on the input 212. In some embodiments, the three-dimensional modelmay have a volume that is defined at least partially by the contoursdrawn by the person. For example, the volume of the three-dimensionalmodel may have a surface that intersects the created contours. Also, insome embodiments, the three-dimensional model may further include afirst layer created automatically by the processor so that the firstlayer surrounds the volume, and a second layer created automatically bythe processor so that the second layer surrounds the first layer. Thefirst layer may have a first pre-determined thickness, and the secondlayer may have a second pre-determined thickness. Also, the processormay assign all voxels inside the volume to have a first color/gray-scale(like the color shown in the region 802 in the template 214 in FIG. 8),all voxels inside the first layer to have a second color/gray-scale(like the color shown in the region 804 in the template 214), and allvoxels inside the second layer to have a third color/gray-scale (likethe color shown in the region 806 in the template 214). After thethree-dimensional model is created, the three-dimensional model may bestored in a non-transitory medium for later processing.

During use, the input image 220 is received by the processor. In orderto cross correlate with the input image 220, the processor reslices thethree-dimensional contour in order to make a two dimensional contourparallel to the input image plane. The reslicing may, for example, bethrough a treatment isocenter (e.g., the center point of the tumor asidentified by the user during planning). To match the geometry of theinput image, the processor may be configured to forward project thistwo-dimensional contour. Then the processor may generate the two layers802, 804 surrounding the contour in the forward projected contour image,thus resulting in a two-dimensional template (like the template 214shown in the example of FIG. 8).

In some embodiments, when performing the method 200 based on markerlessfiducial(s) (e.g., tissue structure), the input image 220 may beprocessed so that the processed image 222 looks like the template image214. For example, in the image processing 204/500, the first filter 510may be applied to highlight a boundary of tissue structure, and thesecond filter 520 may be applied to smooth the features inside theboundary of the tissue structure. As shown in the example of FIG. 8,using such technique, the input image 220 may be processed to achieve aprocessed image 222 having a smeared feature, so that the processedimage 222 resembles the template image 214. In some embodiments, thefirst filter 510 may be a rolling ball filter, and the second filter 520may be a low-pass filter (e.g., a median filter, an average filter,etc.). In other embodiments, the first filter 510 may be another type offilter. For example, in some embodiments that involve markerlessfiducial(s), the first filter 510 may be any type of filter that iscapable of enhancing a boundary of tissue structure. Also, formarkerless fiducial(s), the second filter 520 may be a median filter inone implementation.

After the input image 220 is processed to obtain the processed image222, and after the template image 214 has been obtained, the processedinput image 222 is then compared with the template image 214 in thetemplate matching process 206, like that described previously.

In other embodiments, the input image 220 may be a digital tomosynthesis(DTS) image that is made from multiple angularly adjacent projectionsrather than a single projection. Digital tomosynthesis image is an image(e.g., volumetric image) that is reconstructed using projection images,wherein the number of projection images involved may be less than thosefor a CT image. In such cases, the image processing 204 is optional, andthe DTS input image 220 itself (e.g., a slice of the DTS input image220) may be used for comparison with the template 214. In otherembodiments, the image processing 204 may be performed to enhance afeature in the DTS input image 220 before the enhanced input image iscompared with the template 214. The template 214 for comparison with theinput image 220 may be a DTS image constructed from a CT volumetricimage 210. In such cases the DTS image that forms the template 214 maybe considered an “artificial” DTS image because it is not constructedaccording to conventional technique in which a DTS image isreconstructed from a plurality of projection images.

Various techniques may be used to obtain a set of artificial DTS imagesfrom a volumetric CT image. In some embodiments, the processor (e.g.,the processor 54, or another processor) is configured to computationallyforward project voxels (e.g., those in a region of interest as definedby a user) in the volumetric image 210 onto a set of intermediate planesto create image slices 900 a-900 e (FIG. 9A). In one technique, whenperforming the forward projection to create the image slices 900 a-900e, the processor may mathematically move a simulated source along atrajectory (e.g., an arc path) partially around an object in thevolumetric image 210 to different positions that correspond with theangular spacing of the projections used to form the online DTS image220. Such technique is illustrated graphically in FIG. 9B. As shown inthe figure, the forward projection is performed from different positions910 a-910 g with angular spacing 912. In some embodiments, the angularspacing 912 may be equal to the angular spacing of the projections usedto form the online DTS image 220. In other embodiments, the angularspacing 912 may be different from (e.g., greater than, or less than) theangular spacing of the projections used to form the online DTS image220. To create a slice 900 (e.g., 900 a), forward projection isperformed from the different positions 910 a-910 g onto the plane of theslice 900 (e.g., the plane of slice 900 a). For example, when performingforward projection from position 910 b onto the plane of the image slice900 a, all points along the projection path 930 (including points 940 ain front of the plane of the image slice 900 a, and points 940 b in theback of the plane of the image slice 900 a) through the voxels ofinterest in the volumetric image 210 are projected onto the plane of theimage slice 900 a. Although one projection path 930 is shown in theexample, it should be understood that there may be multiple projectionpaths 930 for any given position 910 that extend from the position 910and that intersect the plane of the slice being created, therebycreating a two dimensional forward projection image onto the plane ofthe slice being created for any given position 910. Forward projectionsare also performed from other positions (e.g., 910 a, 910 c-910 g) ontothe plane of the image slice 900 a. The forward projections at the planeof the image slice 900 a are then summed to create the image slice 900a. The same technique may be repeated to create other image slices 900b-900 e. Although five image slices 900 a-900 e are shown in theexample, in other embodiments, there may be more than five image slices900 or fewer than five image slices. In some cases, the image slices 900a-900 e may be considered as corresponding to an intermediate stage ofback projecting in a DTS reconstruction algorithm.

In some embodiments, the mathematically moving of a simulated source maybe considered to have been performed by the processor when the processorhas performed forward projection from multiple angular positions. Also,in some embodiments, when performing the forward projection, the arccenter for the trajectory 930 of the simulated source may be the same asthe arc center for the trajectory for obtaining the online DTS image220. In addition, in some embodiments, the arc length for the trajectoryof the simulated source may be the same as the arc length for thetrajectory for obtaining the online DTS image 220. In other embodiments,the arc length for the trajectory of the simulated source may bedifferent from (e.g., longer than) the arc length for the trajectory forobtaining the online DTS image 220 for achieving better depthresolution.

In some embodiments, after the image slices 900 a-900 e are formed, theimage slices 900 a-900 e themselves may be used as templates 214. Inother embodiments, the image slices 900 a-900 e may be deblurred tocreate respective deblurred image slices, and the deblurred image slicesare then used as templates 214.

Various techniques may be employed to de-blur the image slices 900 a-900e. In some embodiments, to de-blur a slice 900, the processor maydetermine a blur image contributing from objects in other slices, andmay subtract this blur image from the slice 900 being deblurred. Forexample, to de-blur image slice 900 b, other slices 900 a and 900 c-900e are forward projected onto the plane of the image slice 900 b, and arethen summed to create a blur image for the image slice 900 b. FIG. 9Cillustrates this technique. As shown in the figure, to create a blurimage for slice 900 b, the processor (e.g., the processor 54, or anotherprocessor) is configured to computationally forward project pixels inthe other image slices 900 a and 900 c-900 e onto the plane of the imageslice 900 b. In one technique, when performing the forward projection tocreate the blur image, the processor may mathematically move a simulatedsource along a trajectory 948 (e.g., an arc path) partially around anobject of interest to different positions that correspond with theangular spacing of the projections used to form the online DTS image220. As shown in the figure, the forward projection is performed fromdifferent positions 950 a-950 g with angular spacing 952. In someembodiments, the angular spacing 952 may be equal to the angular spacingof the projections used to form the online DTS image 220. In otherembodiments, the angular spacing 952 may be different from (e.g.,greater than, or less than) the angular spacing of the projections usedto form the online DTS image 220. Also, in some embodiments, the angularspacing 952 for generating the blur image may be the same as the angularspacing 912 for generating the image slices 900. In other embodiments,the angular spacing 952 for generating the blur image may be differentfrom the angular spacing 912 for generating the image slices 900. Tocreate the blur image for the image slice 900 b, forward projection isperformed from the different positions 950 a-950 g onto the plane of theimage slice 900 b. For example, when performing forward projection fromposition 950 b onto the plane of the image slice 900 b, all points alongthe projection path 960 (including points 970 a in front of the plane ofthe image slice 900 b, and points 970 b in the back of the plane of theimage slice 900 b) at the different image slices 900 a and 900 c-900 eare projected onto the plane of the image slice 900 b. Although oneprojection path 960 is shown in the example, it should be understoodthat there may be multiple projection paths 960 for any given position950 that extend from the position 950 and that intersect the plane ofthe slice being de-blurred, thereby creating a two dimensional forwardprojection image onto the plane of the slice being de-blurred for anygiven position 950. Forward projections are also performed from otherpositions (e.g., 950 a, 950 c-950 g) onto the plane of the image slice900 b. The forward projections at the plane of the image slice 900 b arethen summed to create the blur image for the image slice 900 b. Theabove technique may be repeated to create corresponding blur images forthe other respective image slices 900 a and 900 c-900 e.

In some embodiments, the mathematically moving of a simulated sourceduring the de-blurring process may be considered to have been performedby the processor when the processor has performed forward projectionfrom multiple angular positions. Also, in some embodiments, in thede-blurring process, the arc center for the trajectory of the simulatedsource may be the same as the arc center for the trajectory forobtaining the online DTS image 220. In addition, in some embodiments,the arc length for the trajectory of the simulated source may be thesame as the arc length for the trajectory for obtaining the online DTSimage 220. In other embodiments, the arc length for the trajectory ofthe simulated source may be different from (e.g., longer than) the arclength for the trajectory for obtaining the online DTS image 220.

After the blur image is obtained, the processor then subtracts the blurimage from slice 900 b to de-blur the slice 900 b. The same process isperformed to deblur the other slices (e.g., 900 a, and 900 c-900 e) inthe set to result in a set of deblurred image slices. In someembodiments, the deblurred image slices may be stored as the templates214 in a non-transitory medium for later processing (e.g., templatematching with the online image 220).

The above technique results in a set of deblurred slices 900 a-900 ethat form a set of templates 214 for a given gantry angle. In someembodiments, the processor may select a center one of the deblurredslices 900 a-900 e (or one of the slices that is the closest to thecenter) to use for comparison with the online DTS image 220 (e.g., acorresponding slice in the online DTS image 220). In other embodiments,the processor may compare multiple slices of the template 214 tocorresponding multiple slices of the online DTS image 220 to achieve arough three-dimensional matching.

The above technique is better than another possible method in which CTvoxels are forward projected all the way to simulate projection images(rather than the above-described intermediate images) for reconstructionof the reference DTS images, thus saving computation time and resources.Also, the above technique obviates the need to perform a back projection(like that required when a method of generating DRRs is used).

After the input DTS image 220 is obtained (and optionally processed toenhance a feature therein), and after the template image 214 has beenobtained, the input image 220 is then compared with the template image214 in the template matching process 206, like that describedpreviously.

Computer System Architecture

FIG. 10 is a block diagram that illustrates an embodiment of a computersystem 1900 upon which an embodiment of the invention may beimplemented. Computer system 1900 includes a bus 1902 or othercommunication mechanism for communicating information, and a processor1904 coupled with the bus 1902 for processing information. The processor1904 may be an example of the processor 54 of FIG. 1, or anotherprocessor that is used to perform various functions described herein. Insome cases, the computer system 1900 may be used to implement theprocessor 54 (or other processors described herein). The computer system1900 also includes a main memory 1906, such as a random access memory(RAM) or other dynamic storage device, coupled to the bus 1902 forstoring information and instructions to be executed by the processor1904. The main memory 1906 also may be used for storing temporaryvariables or other intermediate information during execution ofinstructions to be executed by the processor 1904. The computer system1900 further includes a read only memory (ROM) 1908 or other staticstorage device coupled to the bus 1902 for storing static informationand instructions for the processor 1904. A data storage device 1910,such as a magnetic disk or optical disk, is provided and coupled to thebus 1902 for storing information and instructions.

The computer system 1900 may be coupled via the bus 1902 to a display1912, such as a cathode ray tube (CRT) or a flat panel, for displayinginformation to a user. An input device 1914, including alphanumeric andother keys, is coupled to the bus 1902 for communicating information andcommand selections to processor 1904. Another type of user input deviceis cursor control 1916, such as a mouse, a trackball, or cursordirection keys for communicating direction information and commandselections to processor 1904 and for controlling cursor movement ondisplay 1912. This input device typically has two degrees of freedom intwo axes, a first axis (e.g., x) and a second axis (e.g., y), thatallows the device to specify positions in a plane.

The computer system 1900 may be used for performing various functions(e.g., calculation) in accordance with the embodiments described herein.According to one embodiment, such use is provided by computer system1900 in response to processor 1904 executing one or more sequences ofone or more instructions contained in the main memory 1906. Suchinstructions may be read into the main memory 1906 from anothercomputer-readable medium, such as storage device 1910. Execution of thesequences of instructions contained in the main memory 1906 causes theprocessor 1904 to perform the process steps described herein. One ormore processors in a multi-processing arrangement may also be employedto execute the sequences of instructions contained in the main memory1906. In alternative embodiments, hard-wired circuitry may be used inplace of or in combination with software instructions to implement theinvention. Thus, embodiments of the invention are not limited to anyspecific combination of hardware circuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to the processor 1904 forexecution. Such a medium may take many forms, including but not limitedto, non-volatile media, volatile media, and transmission media.Non-volatile media includes, for example, optical or magnetic disks,such as the storage device 1910. A non-volatile medium may be consideredas an example of a non-transitory medium. Volatile media includesdynamic memory, such as the main memory 1906. A volatile medium may beconsidered as another example of a non-transitory medium. Transmissionmedia includes coaxial cables, copper wire and fiber optics, includingthe wires that comprise the bus 1902. Transmission media can also takethe form of acoustic or light waves, such as those generated duringradio wave and infrared data communications.

Common forms of computer-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, or any other magneticmedium, a CD-ROM, any other optical medium, punch cards, paper tape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, any other memory chip or cartridge, a carrier wave asdescribed hereinafter, or any other medium from which a computer canread.

Various forms of computer-readable media may be involved in carrying oneor more sequences of one or more instructions to the processor 1904 forexecution. For example, the instructions may initially be carried on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to the computer system 1900can receive the data on the telephone line and use an infraredtransmitter to convert the data to an infrared signal. An infrareddetector coupled to the bus 1902 can receive the data carried in theinfrared signal and place the data on the bus 1902. The bus 1902 carriesthe data to the main memory 1906, from which the processor 1904retrieves and executes the instructions. The instructions received bythe main memory 1906 may optionally be stored on the storage device 1910either before or after execution by the processor 1904.

The computer system 1900 also includes a communication interface 1918coupled to the bus 1902. The communication interface 1918 provides atwo-way data communication coupling to a network link 1920 that isconnected to a local network 1922. For example, the communicationinterface 1918 may be an integrated services digital network (ISDN) cardor a modem to provide a data communication connection to a correspondingtype of telephone line. As another example, the communication interface1918 may be a local area network (LAN) card to provide a datacommunication connection to a compatible LAN. Wireless links may also beimplemented. In any such implementation, the communication interface1918 sends and receives electrical, electromagnetic or optical signalsthat carry data streams representing various types of information.

The network link 1920 typically provides data communication through oneor more networks to other devices. For example, the network link 1920may provide a connection through local network 1922 to a host computer1924 or to equipment 1926 such as a radiation beam source or a switchoperatively coupled to a radiation beam source. The data streamstransported over the network link 1920 can comprise electrical,electromagnetic or optical signals. The signals through the variousnetworks and the signals on the network link 1920 and through thecommunication interface 1918, which carry data to and from the computersystem 1900, are exemplary forms of carrier waves transporting theinformation. The computer system 1900 can send messages and receivedata, including program code, through the network(s), the network link1920, and the communication interface 1918.

It should be noted that, as used in this specification, the term “image”is not necessarily limited to image that is displayed, and may refer toimage that is not displayed as well. For example, in some embodiments,any of the images described herein (e.g., input image 220, processedimage 222, volumetric image 210, template image 214, etc.) may be storedin a non-transitory medium as image data.

Also, the term “processor” may include one or more processing units, andmay refer to any device that is capable of performing mathematicalcomputation implemented using hardware and/or software. The term“processor” may also refer to software stored in a non-transitory mediumin other embodiments. Further, in any of the embodiments describedherein, instead of using the processor 54 to perform the variousfunctions described, a separate processor may be used.

Although particular embodiments have been shown and described, it willbe understood that they are not intended to limit the claimedinventions, and it will be obvious to those skilled in the art thatvarious changes and modifications may be made without departing from thespirit and scope of the claimed inventions. The specification anddrawings are, accordingly, to be regarded in an illustrative rather thanrestrictive sense. The claimed inventions are intended to coveralternatives, modifications, and equivalents.

What is claimed:
 1. A method of generating a template image, comprising:receiving an input from a user, the input comprising objectidentification of bodily tissue in a volumetric image, the volumetricimage having multiple slices; determining a volume-of-interest (VOI) toinclude voxels corresponding to a subset of the volumetric image of thebodily tissue, wherein a size of the VOI is less than a size of thevolumetric image; and determining the template image using at least someof the voxels in the VOI, wherein the act of determining the templateimage comprises performing a forward projection of the at least some ofthe voxels in the VOI using a processor; wherein the act of performingthe forward projection comprises forward projecting the voxels in theVOI while excluding one or more voxels outside the VOI; wherein the VOIis determined before the forward projection is performed, and wherein atleast a part of the VOI has a cross sectional shape that is the samealong a rotational axis of a gantry of a medical device; and wherein theVOI comprises a cylinder, and a cylindrical geometry of the VOI isdefined based on one or more contours of the bodily tissue such that allvoxels within the one or more contours are within the cylindricalgeometry.
 2. The method of claim 1, wherein the forward projectioncomprises a forward maximum intensity projection of the at least some ofthe voxels in the VOI.
 3. The method of claim 1, wherein the forwardprojection comprises a forward average projection of the at least someof the voxels in the VOI.
 4. The method of claim 1, wherein the forwardprojection comprises a forward median projection of the at least some ofthe voxels in the VOI.
 5. The method of claim 1, wherein the act ofdetermining the template image further comprises resampling voxels inthe VOI into image planes that are parallel to a plane of an input imagebefore the forward projection is performed.
 6. The method of claim 1,wherein the template has an image feature that is similar to that in aDTS image.
 7. The method of claim 1, wherein act of determining thetemplate comprises forward projecting the at least some of the voxels inthe VOI to different image slices that are parallel to each other. 8.The method of claim 7, wherein the act of determining the templatefurther comprises performing a de-blurring procedure for each of theimage slices.
 9. The method of claim 1, wherein the cross sectionalshape is perpendicular to the rotational axis.
 10. A computer producthaving a non-transitory medium storing a set of instructions, anexecution of which causes a method to be performed, the methodcomprising: receiving an input from a user, the input comprising objectidentification of bodily tissue in a volumetric image, the volumetricimage having multiple slices; determining a volume-of-interest (VOI) toinclude voxels corresponding to a subset of the volumetric image of thebodily tissue, wherein a size of the VOI is less than a size of thevolumetric image; and determining a template image using at least someof the voxels in the VOI, wherein the act of determining the templateimage comprises performing a forward projection of the at least some ofthe voxels in the VOI; wherein the act of performing the forwardprojection comprises forward projecting the voxels in the VOI whileexcluding one or more voxels outside the VOI; wherein the VOI isdetermined before the forward projection is performed, and wherein atleast a part of the VOI has a cross sectional shape that is the samealong a rotational axis of a gantry of a medical device; and wherein theVOI comprises a cylinder, and a cylindrical geometry of the VOI isdefined based on one or more contours of the bodily tissue such that allvoxels within the one or more contours are within the cylindricalgeometry.
 11. The computer product of claim 10, wherein the forwardprojection comprises a forward maximum intensity projection of the atleast some of the voxels in the VOI.
 12. The computer product of claim10, wherein the forward projection comprises a forward averageprojection of the at least some of the voxels in the VOI.
 13. Thecomputer product of claim 10, wherein the forward projection comprises aforward median projection of the at least some of the voxels in the VOI.14. The computer product of claim 10, wherein the act of determining thetemplate image further comprises resampling voxels in the VOI into imageplanes that are parallel to a plane of an input image before the forwardprojection is performed.
 15. The computer product of claim 10, whereinthe template has an image feature that is similar to that in a DTSimage.
 16. The computer product of claim 10, wherein act of determiningthe template comprises forward projecting the at least some of thevoxels in the VOI to different image slices that are parallel to eachother.
 17. The computer product of claim 16, wherein the act ofdetermining the template further comprises performing a de-blurringprocedure for each of the image slices.
 18. The computer product ofclaim 17, wherein the cross sectional shape is perpendicular to therotational axis.